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Record W2285078778 · doi:10.1139/cgj-2014-0324

Experimental characterization of deformation, coefficient of earth pressure at rest, stiffness, and contact force distributions of sand during secondary compression and rebound

2015· article· en· W2285078778 on OpenAlexvenueno aff
Yongsheng Gao, Yu-Hsing Wang

Bibliographic record

VenueCanadian Geotechnical Journal · 2015
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Soil Mechanics
Canadian institutionsnot available
FundersMinistère de l'Enseignement supérieur, de la Recherche et de l'Innovation
KeywordsStiffnessCompression (physics)Deformation (meteorology)Geotechnical engineeringOverburden pressureStress (linguistics)Lateral earth pressureMathematicsMaterials scienceGeologyComposite material

Abstract

fetched live from OpenAlex

This paper aims to provide a comprehensive picture of the sand responses during secondary compression and rebound based on experimental characterizations. The experiment was carried out on dry Leighton Buzzard sand using a modified direct shear box equipped with tactile pressure sensors for the stress measurements and bender elements for stiffness (i.e., Ghv and Ghh) monitoring. It was found that secondary compression and rebound followed the same deformation trends as primary compression and rebound to continuously contract and expand, respectively. The deformation characteristics determined the changes in the associated soil properties; therefore, the opposite soil behavior during secondary compression and rebound was observed. During secondary compression, the corresponding void change, deviatoric strains εq, and the deviatoric strain rate [Formula: see text] increased with increasing vertical stress [Formula: see text] or deviatoric stress q because the sample crept more easily under a higher [Formula: see text] or q. The compression deformation gave rise to an increase in the horizontal stress [Formula: see text] and associated coefficient of earth pressure at rest K0. The soil stiffness also increased as the contact normal forces became more homogenized. During secondary rebound, the sample expanded unabated no matter whether [Formula: see text] was greater or smaller than [Formula: see text]. The corresponding void ratio change, εq, and [Formula: see text] increased with decreasing [Formula: see text] or q because the sample expanded more easily under a lower [Formula: see text] or q. The expansion gradually reduced [Formula: see text] along with the associated K0 value. The sample stiffness continued to decrease, and contact force homogenization was not observed.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.008
GPT teacher head0.191
Teacher spread0.183 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations8
Published2015
Admission routes1
Has abstractyes

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